Advertisement

Journal of Child and Family Studies

, Volume 28, Issue 5, pp 1263–1271 | Cite as

Do Attachment Styles and Family Functioning Predict Adolescents’ Problematic Internet Use? A Relative Weight Analysis

  • Marco Cacioppo
  • Daniela Barni
  • Cinzia Correale
  • Sonia Mangialavori
  • Francesca Danioni
  • Alessio GoriEmail author
Original Paper

Abstract

Objectives

The increased use of Internet in the last decade has led to problematic behaviour that can affect people’s individual and social functioning, especially among younger individuals. This study aimed to explore the relation between problematic Internet use (PIU), attachment style, and perception of family functioning in adolescence.

Methods

Participants were 306 Italian adolescents (62.7% females and 37.3% males) aged from 15 to 18 years (M = 16.07, SD = 0.91). Participants completed the following measures: the Young’s Internet Addiction Test (Y-IAT), the Relationship Questionnaire (RQ), and the Family Assessment Device (FAD).

Results

The results of regression and relative weight analyses showed that family functioning and attachment styles were important predictors of adolescent PIU. In particular, a greater perception of family members as being interested in and placing value on each other’s activities and concerns (i.e., affective involvement) and a greater perception that tasks were clearly and equitably assigned to family members (i.e., roles) were associated with less PIU. In contrast, a greater anxious-preoccupied attachment was associated with a greater risk of PIU.

Conclusions

In line with these results, it would be recommendable the development of family-focused prevention programs for all adolescents at risk of PIU before they develop a full Internet addiction. Further research on this topic is needed to develop a specific, autonomous, and comprehensive diagnostic process for PIU to avoid conceptual and treatment overlap between PIU and other kinds of addictive behaviors.

Keywords

Problematic internet use Addiction Attachment styles Family functioning Adolescents 

Notes

Acknowledgements

We thank Diane Williams, PhD, from Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.

Author Contributions

M.C. designed and executed the study, assisted with the data analyses, and wrote the paper. D.B. and S.M. analyzed the data and collaborated in the writing of the manuscript. F.D. and C.C. collaborated in the design and writing of the study. A.G. collaborated in the writing and editing of the final manuscript.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. LUMSA University of Rome provided IRB approval for this study.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Anderson, E. L., Steen, E., & Stavropoulos, V. (2017). Internet use and problematic internet use: A systematic review of longitudinal research trends in adolescence and emergent adulthood. International Journal of Adolescence and Youth, 22, 430–454.CrossRefGoogle Scholar
  2. Atwood, R. M., Beckert, T. E., & Rhodes, M. R. (2017). Adolescent problematic digital behaviors associated with mobile devices. North American Journal of Psychology, 19, 659–684.Google Scholar
  3. Barni, D. (2015). Relative importance analysis for the study of the family: Accepting the challenge of correlated predictors. TPM: Testing, Psychometrics, Methodology in Applied Psychology, 22, 235–250.Google Scholar
  4. Bartholomew, K., & Horowitz, L. (1991). Attachment styles among young adults: A test of a four-category model. Journal of Personality and Social Psychology, 61, 226–244.CrossRefGoogle Scholar
  5. Bartholomew, K., & Shaver, P. R. (1998). Methods of assessing adult attachment. Attachment theory and close relationships. In J. A. Simpson & W. S. Rholes (Eds.), Attachment theory and close relationships (pp. 25–45). New York, NY: Guilford Press.Google Scholar
  6. Billieux, J., Schimmenti, A., Khazaal, Y., Maurage, P., & Heeren, A. (2015). Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. Journal of Behavioral Addictions, 4, 119–123.CrossRefGoogle Scholar
  7. Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner (Ed.), Handbook of child psychology: Theoretical models of human development. 6th ed. (pp. 793–828). Hoboken, NJ: Wiley. Vol. 1.Google Scholar
  8. Cacioppo, M., Pace, U., & Zappulla, C. (2013). Parental psychological control, quality of family context and life satisfaction among Italian adolescents. Child Indicators Research, 6, 179–191.CrossRefGoogle Scholar
  9. Campanella, M., Mucci, F., Baroni, S., Nardi, L., & Marazziti, D. (2015). Prevalence of internet addiction: A pilot study in a group of Italian high-school students. Clinical Neuropsychiatry, 12, 90–93.Google Scholar
  10. Carvalho, J., Francisco, R., & Relvas, A. (2015). Family functioning and information and communication technologies: How do they relate? A literature review. Computers in Human Behavior, 45, 99–108.CrossRefGoogle Scholar
  11. Casale, S., & Fioravanti, G. (2011). Psychosocial correlates of internet use among Italian students. International Journal of Psychology, 46, 288–298.CrossRefGoogle Scholar
  12. Chen, Y. L., Chen, S. H., & Gau, S. F. S. (2015). ADHD and autistic traits, family function, parenting style, and social adjustment for internet addiction among children and adolescents in Taiwan: A longitudinal study. Research in Developmental Disabilities, 39, 20–31.CrossRefGoogle Scholar
  13. Cho, S. M., Sung, M. J., Shin, K. M., Lim, K. Y., & Shin, Y. M. (2013). Does psychopathology in childhood predict internet addiction in male adolescents? Child Psychiatry & Human Development, 44, 549–555.CrossRefGoogle Scholar
  14. Choo, H., Sim, T., Liau, A. K. F., Gentile, D. A., & Khoo, A. (2015). Parental influences on pathological symptoms of videogaming among children and adolescents: A prospective study. Journal of Child and Family Studies, 24, 1429–1441.CrossRefGoogle Scholar
  15. Ciarrochi, J., Parker, P., Sahdra, B., Marshall, S., Jackson, C., Gloster, A. T., & Heaven, P. (2016). The development of compulsive internet use and mental health: A four-year study of adolescence. Developmental Psychology, 52, 271–283.CrossRefGoogle Scholar
  16. Epstein, N., Baldwin, L., & Bishop, D. (1983). The McMaster Family Assessment Device. Journal of Marital and Family Therapy, 9, 171–180.CrossRefGoogle Scholar
  17. Faraci, P., Craparo, G., Messina, R., & Severino, S. (2013). Internet Addiction Test (IAT): Which is the best factorial solution? Journal of Medical Internet Research, 15, e225.CrossRefGoogle Scholar
  18. Gámez-Guadix, M., Calvete, E., Orue, I., & Havas, C. L. (2015). Problematic internet use and problematic alcohol use from the cognitive–behavioral model: A longitudinal study among adolescents. Addictive Behaviours, 40, 109–114.CrossRefGoogle Scholar
  19. Gámez-Guadix, M., Orue, I., Smith, P. K., & Calvete, E. (2013). Longitudinal and reciprocal relations of cyberbullying with depression, substance use, and problematic internet use among adolescents. Journal of Adolescent Health, 53, 446–452.CrossRefGoogle Scholar
  20. Griffin, D. W., & Bartholomew, K. (1994). The metaphysics of measurement: The case of adult attachment. In K. Bartholomew & D. Perlman (Eds.), Attachment processes in adulthood (pp. 17–52). London: Jessica Kingsley.Google Scholar
  21. Hong, S., You, S., Kim, E., & No, U. (2014). A group-based modeling approach to estimating longitudinal trajectories of Korean adolescents’ on-line game time. Personality and Individual Differences, 59, 9–15.CrossRefGoogle Scholar
  22. Johnson, J. (2000). A heuristic method for estimating the relative weight of predictor variables in multiple regression. Multivariate Behavioral Research, 35, 1–19.CrossRefGoogle Scholar
  23. Ko, C. H., Liu, G. C., Hsiao, S., Yen, J. Y., Yang, M. J., Lin, W. C., & Chen, C. S. (2009). Brain activities associated with gaming urge of online gaming addiction. Journal of Psychiatric Research, 43, 739–747.CrossRefGoogle Scholar
  24. Ko, C., Yen, J., Yen, C., Lin, H., & Yang, M. (2007). Factors predictive for incidence and remission of internet addiction in young adolescents: A prospective study. Cyberpsychology & Behavior, 10, 545–551.CrossRefGoogle Scholar
  25. Kraha, A., Turner, H., Nimon, K., Zientek, L., & Henson, R. (2012). Tools to support interpreting multiple regression in the face of multicollinearity. Frontiers in Psychology, 3, 44.CrossRefGoogle Scholar
  26. Laghi, F., Schneider, B. H., Vitoroulis, I., Coplan, R. J., Baiocco, R., Amichai-Hamburger, Y., Hudek, N., Koszycki, D., Miller, S., & Flament, M. (2013). Knowing when not to use the Internet: Shyness and adolescents’ on-line and off-line interactions with friends. Computers in Human Behavior, 29(1), 51–57.CrossRefGoogle Scholar
  27. Lanigan, J. (2009). A sociotechnological model for family research and intervention: How information and communication technologies affect family life. Marriage & Family Review, 45, 587–609.CrossRefGoogle Scholar
  28. Li, W., O’Brien, J., Snyder, S., & Howard, M. (2015). Characteristics of internet addiction/pathological internet use in U.S. university students: A qualitative-method investigation. PLoS One, 10, e0117372.CrossRefGoogle Scholar
  29. Lin, M., Ko, H., & Wu, J. (2011). Prevalence and psychosocial risk factors associated with internet addiction in a nationally representative sample of college students in Taiwan. Cyberpsychology, Behavior, and Social Networking, 14, 741–746.CrossRefGoogle Scholar
  30. Lin, S., & Tsai, C. (2002). Sensation seeking and internet dependence of Taiwanese high school adolescents. Computers in Human Behavior, 18, 411–426.CrossRefGoogle Scholar
  31. Lipovetsky, S., & Coklin, W. M. (2015). Predictor relative importance and matching regression parameters. Journal of Applied Statistics, 42, 1017–1031.CrossRefGoogle Scholar
  32. Mittal, V. A., Dean, D. J., & Pelletier, A. (2013). Internet addiction, reality substitution and longitudinal changes in psychotic-like experiences in young adults. Early Intervention Psychiatry, 7, 261–269.CrossRefGoogle Scholar
  33. Odacı, H., & Çıkrıkçı, Ö. (2014). Problematic internet use in terms of gender, attachment styles and subjective well-being in university students. Computers in Human Behavior, 32, 61–66.CrossRefGoogle Scholar
  34. Pace, U., Zappulla, C., & Di Maggio, R. (2016). The mediating role of perceived peer support in the relation between quality of attachment and internalizing problems in adolescence: A longitudinal perspective. Attachment & Human Development, 18, 508–524.CrossRefGoogle Scholar
  35. Park, S., Kim, J. Y., & Cho, C. B. (2008). Prevalence of internet addiction and correlations with family factors among South Korean adolescents. Adolescence, 43, 895–909.Google Scholar
  36. Pempek, T. A., & McDaniel, B. T. (2016). Young children’s tablet use and associations with maternal well-being. Journal of Child and Family Studies, 25, 2636–2647.CrossRefGoogle Scholar
  37. Roncone, R., Rossi, L., Muiere, E., Impallomeni, M., Matteucci, M., Giacomelli, R., & Casacchia, M. (1998). The Italian version of the family assessment device. Social Psychiatry and Psychiatric Epidemiology, 33, 451–461.CrossRefGoogle Scholar
  38. Schimmenti, A., Passanisi, A., Caretti, V., La Marca, L., Granieri, A., & Iacolino, C. (2017). Traumatic experiences, alexithymia, and internet addiction symptoms among late adolescents: A moderated mediation analysis. Addictive Behaviors, 64, 314–320.CrossRefGoogle Scholar
  39. Schimmenti, A., Passanisi, A., Gervasi, A., Manzella, S., & Famà, F. (2013). Insecure attachment attitudes in the onset of problematic internet use among late adolescents. Child Psychiatry & Human Development, 45, 588–595.CrossRefGoogle Scholar
  40. Schimmenti, A., Guglielmucci, F., Barbasio, C., & Granieri, A. (2012). Attachment disorganization and dissociation in virtual worlds: A study on problematic internet use among players of online role playing games. Clinical Neuropsychiatry, 9, 195–202.Google Scholar
  41. Schimmenti, A., & Caretti, V. (2010). Psychic retreats or psychic pits? Unbearable states of mind and technological addiction. Psychoanal Psychol, 27, 115–132.CrossRefGoogle Scholar
  42. Şenormancı, Ö., Şenormancı, G., Güçlü, O., & Konkan, R. (2014). Attachment and family functioning in patients with internet addiction. General Hospital Psychiatry, 36, 203–207.CrossRefGoogle Scholar
  43. Shapira, N., Lessig, M., Goldsmith, T., Szabo, S., Lazoritz, M., Gold, M., & Stein, D. (2003). Problematic internet use: Proposed classification and diagnostic criteria. Depression and Anxiety, 17, 207–216.CrossRefGoogle Scholar
  44. Stavropoulos, V., Gentile, D., & Motti-Stefanidi, F. (2016). A multilevel longitudinal study of adolescent internet addiction: The role of obsessive–compulsive symptoms and classroom openness to experience. European Journal of Developmental Psychology, 13, 99–114.CrossRefGoogle Scholar
  45. Stavropoulos, V., Kuss, D. J., Griffiths, M. D., Wilson, P., & Motti-Stefanidi, F. (2017). MMORPG gaming and hostility predict internet addiction symptoms in adolescents: An empirical multilevel longitudinal study. Addictive Behaviours, 64, 294–300.CrossRefGoogle Scholar
  46. Sun, P., Johnson, C. A., Palmer, P., Arpawong, T. E., Unger, J. B., Xie, B., & Sussman, S. (2012). Concurrent and predictive relationships between compulsive internet use and substance use: Findings from vocational high school students in China and the USA. International Journal of Environmental Research and Public Health, 9, 660–673.CrossRefGoogle Scholar
  47. Tonidandel, S., & LeBreton, J. M. (2010). Determining the relative importance of predictors in logistic regression: An extension of relative weights analysis. Organizational Research Methods, 13, 767–781.CrossRefGoogle Scholar
  48. Van den Eijnden, R. J., Spijkerman, R., Vermulst, A. A., van Rooij, T. J., & Engels, R. C. (2010). Compulsive internet use among adolescents: Bidirectional parent–child relationships. Journal of Abnormal Child Psychology, 38, 77–89.CrossRefGoogle Scholar
  49. Van Rooij, A. J., Schoenmakers, T. M., Vermulst, A. A., Van Den Eijnden, R. J., & Van De Mheen, D. (2011). Online video game addiction: Identification of addicted adolescent gamers. Addiction, 106, 205–212.CrossRefGoogle Scholar
  50. Wartberg, L., Petersen, K. U., Kammerl, R., Rosenkranz, M., & Thomasius, R. (2014). Psychometric validation of a German version of the Compulsive Internet Use Scale. Cyberpsychology, Behavior, and Social Networking, 17, 99–103.CrossRefGoogle Scholar
  51. Willoughby, T. (2008). A short-term longitudinal study of internet and computer game use by adolescent boys and girls: Prevalence, frequency of use, and psychosocial predictors. Developmental Psychology, 44, 195–204.CrossRefGoogle Scholar
  52. Young, K. (1998). Internet addiction: The emergence of a new clinical disorder. Cyberpsychology & Behavior, 1, 237–244.CrossRefGoogle Scholar
  53. Young, K. (2004). Internet addiction. American Behavioral Scientist, 48, 402–415.CrossRefGoogle Scholar
  54. Young, K., & Rogers, R. (1998). The relationship between depression and internet addiction. Cyberpsychology & Behavior, 1, 25–28.CrossRefGoogle Scholar
  55. Yu, C., Li, X., & Zhang, W. (2015). Predicting adolescent problematic online game use from teacher autonomy support, basic psychological needs satisfaction, and school engagement: A 2-year longitudinal study. Cyberpsychology, Behavior, and Social Networking, 18, 228–233.CrossRefGoogle Scholar
  56. Yu, L., & Shek, D. T. (2013). Internet addiction in Hong Kong adolescents: A three-year longitudinal study. Journal of Pediatric & Adolescent Gynecology, 26, S10–S17.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Human SciencesLUMSA University of RomeRomeItaly
  2. 2.Family Studies and Research University CentreCatholic University of MilanMilanItaly

Personalised recommendations